Scheduling: Theory and Algorithms

What it is about

You will learn models and algorithms for the assignment of tasks to scarce resources. The module covers classical and modern scheduling problems (including stochastic, online, robust) as well as methods for their modeling, analysis and solution, so that you can, in the end, assess complexity, design exact or approximate algorithms and prove their quality.

What you will be able to do

• Know fundamental scheduling problems
• Classify and model problems
• Perform complexity analyses (e.g. prove NP-hardness)
• Design optimal algorithms
• Design approximation algorithms and prove approximation factors
• Evaluate worst-case performance of algorithms

What the module consists of

• VorlesungConveying theory, models and algorithms with examples and discussions
• ÜbungDeepening the content through exercises with solutions and feedback

Teaching method

• Vorlesung mit Beispielen und Diskussionto introduce the concepts and to foster independent engagement with the literature
• Übungsaufgaben und Musterlösungento deepen understanding, apply methods and self-check learning progress
• Zusätzliche Medien (Slides, Videoclips)to support the learning process and illustrate concepts